{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 准备工作\n",
    "\n",
    "1.确保您按照[README](README-CN.md)中的说明在环境中设置了API密钥\n",
    "\n",
    "2.安装依赖包"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
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     ]
    }
   ],
   "source": [
    "!pip install tiktoken openai pandas matplotlib plotly scikit-learn numpy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1. 生成 Embedding (基于 text-embedding-ada-002 模型)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "嵌入对于处理自然语言和代码非常有用，因为其他机器学习模型和算法（如聚类或搜索）可以轻松地使用和比较它们。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![Embedding](images/embedding-vectors.svg)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 亚马逊美食评论数据集(amazon-fine-food-reviews)\n",
    "\n",
    "Source:[美食评论数据集](https://www.kaggle.com/snap/amazon-fine-food-reviews)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![dataset](images/amazon-fine-food-reviews.png)\n",
    "\n",
    "\n",
    "该数据集包含截至2012年10月用户在亚马逊上留下的共计568,454条美食评论。为了说明目的，我们将使用该数据集的一个子集，其中包括最近1,000条评论。这些评论都是用英语撰写的，并且倾向于积极或消极。每个评论都有一个产品ID、用户ID、评分、标题（摘要）和正文。\n",
    "\n",
    "我们将把评论摘要和正文合并成一个单一的组合文本。模型将对这个组合文本进行编码，并输出一个单一的向量嵌入。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 导入 pandas 包。Pandas 是一个用于数据处理和分析的 Python 库\n",
    "# 提供了 DataFrame 数据结构，方便进行数据的读取、处理、分析等操作。\n",
    "import pandas as pd\n",
    "# 导入 tiktoken 库。Tiktoken 是 OpenAI 开发的一个库，用于从模型生成的文本中计算 token 数量。\n",
    "import tiktoken"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 加载数据集"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Time</th>\n",
       "      <th>ProductId</th>\n",
       "      <th>UserId</th>\n",
       "      <th>Score</th>\n",
       "      <th>Summary</th>\n",
       "      <th>Text</th>\n",
       "      <th>combined</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1351123200</td>\n",
       "      <td>B003XPF9BO</td>\n",
       "      <td>A3R7JR3FMEBXQB</td>\n",
       "      <td>5</td>\n",
       "      <td>where does one  start...and stop... with a tre...</td>\n",
       "      <td>Wanted to save some to bring to my Chicago fam...</td>\n",
       "      <td>Title: where does one  start...and stop... wit...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1351123200</td>\n",
       "      <td>B003JK537S</td>\n",
       "      <td>A3JBPC3WFUT5ZP</td>\n",
       "      <td>1</td>\n",
       "      <td>Arrived in pieces</td>\n",
       "      <td>Not pleased at all. When I opened the box, mos...</td>\n",
       "      <td>Title: Arrived in pieces; Content: Not pleased...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Time   ProductId          UserId  Score  \\\n",
       "0  1351123200  B003XPF9BO  A3R7JR3FMEBXQB      5   \n",
       "1  1351123200  B003JK537S  A3JBPC3WFUT5ZP      1   \n",
       "\n",
       "                                             Summary  \\\n",
       "0  where does one  start...and stop... with a tre...   \n",
       "1                                  Arrived in pieces   \n",
       "\n",
       "                                                Text  \\\n",
       "0  Wanted to save some to bring to my Chicago fam...   \n",
       "1  Not pleased at all. When I opened the box, mos...   \n",
       "\n",
       "                                            combined  \n",
       "0  Title: where does one  start...and stop... wit...  \n",
       "1  Title: Arrived in pieces; Content: Not pleased...  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "input_datapath = \"data/fine_food_reviews_1k.csv\"\n",
    "df = pd.read_csv(input_datapath, index_col=0)\n",
    "df = df[[\"Time\", \"ProductId\", \"UserId\", \"Score\", \"Summary\", \"Text\"]]\n",
    "df = df.dropna()\n",
    "\n",
    "# 将 \"Summary\" 和 \"Text\" 字段组合成新的字段 \"combined\"\n",
    "df[\"combined\"] = (\n",
    "    \"Title: \" + df.Summary.str.strip() + \"; Content: \" + df.Text.str.strip()\n",
    ")\n",
    "df.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0      Title: where does one  start...and stop... wit...\n",
       "1      Title: Arrived in pieces; Content: Not pleased...\n",
       "2      Title: It isn't blanc mange, but isn't bad . ....\n",
       "3      Title: These also have SALT and it's not sea s...\n",
       "4      Title: Happy with the product; Content: My dog...\n",
       "                             ...                        \n",
       "995    Title: Delicious!; Content: I have ordered the...\n",
       "996    Title: Good Training Treat; Content: My dog wi...\n",
       "997    Title: Jamica Me Crazy Coffee; Content: Wolfga...\n",
       "998    Title: Party Peanuts; Content: Great product f...\n",
       "999    Title: I love Maui Coffee!; Content: My first ...\n",
       "Name: combined, Length: 1000, dtype: object"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[\"combined\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Embedding 模型关键参数"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 模型类型\n",
    "# 建议使用官方推荐的第二代嵌入模型：text-embedding-ada-002\n",
    "embedding_model = \"text-embedding-ada-002\"\n",
    "# text-embedding-ada-002 模型对应的分词器（TOKENIZER）\n",
    "embedding_encoding = \"cl100k_base\"\n",
    "# text-embedding-ada-002 模型支持的输入最大 Token 数是8191，向量维度 1536\n",
    "# 在我们的 DEMO 中过滤 Token 超过 8000 的文本\n",
    "max_tokens = 8000  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 将样本减少到最近的1,000个评论，并删除过长的样本\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1000"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 设置要筛选的评论数量为1000\n",
    "top_n = 1000\n",
    "# 对DataFrame进行排序，基于\"Time\"列，然后选取最后的2000条评论。\n",
    "# 这个假设是，我们认为最近的评论可能更相关，因此我们将对它们进行初始筛选。\n",
    "df = df.sort_values(\"Time\").tail(top_n * 2) \n",
    "# 丢弃\"Time\"列，因为我们在这个分析中不再需要它。\n",
    "df.drop(\"Time\", axis=1, inplace=True)\n",
    "# 从'embedding_encoding'获取编码\n",
    "encoding = tiktoken.get_encoding(embedding_encoding)\n",
    "\n",
    "# 计算每条评论的token数量。我们通过使用encoding.encode方法获取每条评论的token数，然后把结果存储在新的'n_tokens'列中。\n",
    "df[\"n_tokens\"] = df.combined.apply(lambda x: len(encoding.encode(x)))\n",
    "\n",
    "# 如果评论的token数量超过最大允许的token数量，我们将忽略（删除）该评论。\n",
    "# 我们使用.tail方法获取token数量在允许范围内的最后top_n（1000）条评论。\n",
    "df = df[df.n_tokens <= max_tokens].tail(top_n)\n",
    "\n",
    "# 打印出剩余评论的数量。\n",
    "len(df)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 生成 Embeddings 并保存\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "from openai import OpenAI"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "# OpenAI Python SDK v1.0 更新后的使用方式\n",
    "client = OpenAI()\n",
    "\n",
    "# 使用OpenAI代理方式，需要修改base_url\n",
    "# client = OpenAI(\n",
    "#     api_key=\"XXX\", # 你的KEY\n",
    "#     base_url=\"https://vip.apiyi.com/v1\"\n",
    "# )\n",
    "\n",
    "# 替换为国内大模型 API 地址\n",
    "# # 智谱API调用(glm-4v-flash)\n",
    "# openai = OpenAI(\n",
    "#     api_key=\"XXX\",\n",
    "#     base_url=\"https://open.bigmodel.cn/api/paas/v4/\"\n",
    "# )\n",
    "# DeepSeek API调用（deepseek-chat）\n",
    "# openai = OpenAI(\n",
    "#     api_key=\"XXX\",\n",
    "#     base_url=\"https://api.deepseek.com\"\n",
    "# )\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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     ]
    }
   ],
   "source": [
    "# 新版本创建 Embedding 向量的方法\n",
    "# Ref：https://community.openai.com/t/embeddings-api-documentation-needs-to-updated/475663\n",
    "res = client.embeddings.create(input=\"abc\", model=embedding_model)\n",
    "print(res.data[0].embedding)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 使用新方法调用 OpenAI Embedding API\n",
    "def embedding_text(text, model=\"text-embedding-ada-002\"):\n",
    "    res = client.embeddings.create(input=text, model=model)\n",
    "    return res.data[0].embedding"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "### 注意：如果未使用信用卡支付过 OpenAI 账单的同学，可以直接跳过此步骤。\n",
    "\n",
    "### 提醒：非必须步骤，可直接复用项目中的嵌入文件 fine_food_reviews_with_embeddings_1k\n",
    "\n",
    "对于免费试用用户的前48小时，OpenAI 设置了 [速率限制](https://platform.openai.com/docs/guides/rate-limits/overview)\n",
    "\n",
    "如果你已经支付过 OpenAI API 账单，可以尝试取消注释，调用以下代码测试批量 Embedding："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 实际生成会耗时几分钟，逐行调用 OpenAI Embedding API\n",
    "\n",
    "# df[\"embedding\"] = df.combined.apply(embedding_text)\n",
    "# output_datapath = \"data/fine_food_reviews_with_embeddings_1k_1126.csv\"\n",
    "# df.to_csv(output_datapath)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "# e0 = df[\"embedding\"][0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "# e0"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2.读取 fine_food_reviews_with_embeddings_1k 嵌入文件"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "embedding_datapath = \"data/fine_food_reviews_with_embeddings_1k.csv\"\n",
    "\n",
    "df_embedded = pd.read_csv(embedding_datapath, index_col=0)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 查看 Embedding 结果"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "12     [-0.0005399271612986922, -0.004124758299440145...\n",
       "13     [0.0068963742814958096, 0.0167608093470335, -0...\n",
       "14     [-0.0023715533316135406, -0.021357767283916473...\n",
       "15     [0.00226533692330122, 0.010306870564818382, 0....\n",
       "16     [-0.027459919452667236, -0.009041198529303074,...\n",
       "                             ...                        \n",
       "447    [0.00796585250645876, 0.0017102764686569571, 0...\n",
       "436    [0.001777207711711526, -0.011673098430037498, ...\n",
       "437    [-0.005498920567333698, -0.014834611676633358,...\n",
       "438    [-0.00294404081068933, -0.007058987859636545, ...\n",
       "439    [-0.006043732166290283, -0.000693734094966203,...\n",
       "Name: embedding, Length: 1000, dtype: object"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_embedded[\"embedding\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "34410"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(df_embedded[\"embedding\"][0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "str"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(df_embedded[\"embedding\"][0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    },
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
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-0.002689831657335162, -0.03731733188033104, -0.03398984670639038, 0.01527618058025837, -0.023168645799160004, -0.01607367768883705, -0.0135436886921525, 0.005465600173920393, 0.01671992428600788, 0.01865866594016552, 0.0028548308182507753, -0.001274447306059301, -0.019153663888573647, -0.015674928203225136, 0.015014932490885258, -0.012670567259192467, -0.00842871144413948, -0.04353230446577072, 0.007796214893460274, 0.011886821128427982, -0.04218481108546257, -0.014767433516681194, 0.006569033022969961, -0.00963183119893074, -0.011027449741959572, 0.009961829520761967, 0.02125740423798561, -0.002842799760401249, -0.0033446722663939, 0.02157365158200264, -0.03264235332608223, -0.002664050552994013, 0.029094869270920753, 0.0015253836754709482, -0.007005593273788691, -0.021876150742173195, -0.037564828991889954]'"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_embedded[\"embedding\"][0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "import ast\n",
    "\n",
    "# 将字符串转换为向量\n",
    "df_embedded[\"embedding_vec\"] = df_embedded[\"embedding\"].apply(ast.literal_eval)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1536"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(df_embedded[\"embedding_vec\"][0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ProductId</th>\n",
       "      <th>UserId</th>\n",
       "      <th>Score</th>\n",
       "      <th>Summary</th>\n",
       "      <th>Text</th>\n",
       "      <th>combined</th>\n",
       "      <th>n_tokens</th>\n",
       "      <th>embedding</th>\n",
       "      <th>embedding_vec</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>B000K8T3OQ</td>\n",
       "      <td>AK43Y4WT6FFR3</td>\n",
       "      <td>1</td>\n",
       "      <td>Broken in a million pieces</td>\n",
       "      <td>Chips were broken into small pieces. Problem i...</td>\n",
       "      <td>Title: Broken in a million pieces; Content: Ch...</td>\n",
       "      <td>120</td>\n",
       "      <td>[-0.0005399271612986922, -0.004124758299440145...</td>\n",
       "      <td>[-0.0005399271612986922, -0.004124758299440145...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>B0051C0J6M</td>\n",
       "      <td>AWFA8N9IXELVH</td>\n",
       "      <td>1</td>\n",
       "      <td>Deceptive description</td>\n",
       "      <td>On Oct 9 I ordered from a different vendor the...</td>\n",
       "      <td>Title: Deceptive description; Content: On Oct ...</td>\n",
       "      <td>157</td>\n",
       "      <td>[0.0068963742814958096, 0.0167608093470335, -0...</td>\n",
       "      <td>[0.0068963742814958096, 0.0167608093470335, -0...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     ProductId         UserId  Score                     Summary  \\\n",
       "12  B000K8T3OQ  AK43Y4WT6FFR3      1  Broken in a million pieces   \n",
       "13  B0051C0J6M  AWFA8N9IXELVH      1       Deceptive description   \n",
       "\n",
       "                                                 Text  \\\n",
       "12  Chips were broken into small pieces. Problem i...   \n",
       "13  On Oct 9 I ordered from a different vendor the...   \n",
       "\n",
       "                                             combined  n_tokens  \\\n",
       "12  Title: Broken in a million pieces; Content: Ch...       120   \n",
       "13  Title: Deceptive description; Content: On Oct ...       157   \n",
       "\n",
       "                                            embedding  \\\n",
       "12  [-0.0005399271612986922, -0.004124758299440145...   \n",
       "13  [0.0068963742814958096, 0.0167608093470335, -0...   \n",
       "\n",
       "                                        embedding_vec  \n",
       "12  [-0.0005399271612986922, -0.004124758299440145...  \n",
       "13  [0.0068963742814958096, 0.0167608093470335, -0...  "
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_embedded.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3. 使用 t-SNE 可视化 1536 维 Embedding 美食评论"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 导入 NumPy 包，NumPy 是 Python 的一个开源数值计算扩展。这种工具可用来存储和处理大型矩阵，\n",
    "# 比 Python 自身的嵌套列表（nested list structure)结构要高效的多。\n",
    "import numpy as np\n",
    "# 从 matplotlib 包中导入 pyplot 子库，并将其别名设置为 plt。\n",
    "# matplotlib 是一个 Python 的 2D 绘图库，pyplot 是其子库，提供了一种类似 MATLAB 的绘图框架。\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib\n",
    "\n",
    "# 从 sklearn.manifold 模块中导入 TSNE 类。\n",
    "# TSNE (t-Distributed Stochastic Neighbor Embedding) 是一种用于数据可视化的降维方法，尤其擅长处理高维数据的可视化。\n",
    "# 它可以将高维度的数据映射到 2D 或 3D 的空间中，以便我们可以直观地观察和理解数据的结构。\n",
    "from sklearn.manifold import TSNE"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pandas.core.series.Series"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(df_embedded[\"embedding_vec\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 首先，确保你的嵌入向量都是等长的\n",
    "assert df_embedded['embedding_vec'].apply(len).nunique() == 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 将嵌入向量列表转换为二维 numpy 数组\n",
    "matrix = np.vstack(df_embedded['embedding_vec'].values)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 创建一个 t-SNE 模型，t-SNE 是一种非线性降维方法，常用于高维数据的可视化。\n",
    "# n_components 表示降维后的维度（在这里是2D）\n",
    "# perplexity 可以被理解为近邻的数量\n",
    "# random_state 是随机数生成器的种子\n",
    "# init 设置初始化方式\n",
    "# learning_rate 是学习率。\n",
    "tsne = TSNE(n_components=2, perplexity=15, random_state=42, init='random', learning_rate=200)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 使用 t-SNE 对数据进行降维，得到每个数据点在新的2D空间中的坐标\n",
    "vis_dims = tsne.fit_transform(matrix)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 定义了五种不同的颜色，用于在可视化中表示不同的等级\n",
    "colors = [\"red\", \"darkorange\", \"gold\", \"turquoise\", \"darkgreen\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 从降维后的坐标中分别获取所有数据点的横坐标和纵坐标\n",
    "x = [x for x,y in vis_dims]\n",
    "y = [y for x,y in vis_dims]\n",
    "\n",
    "# 根据数据点的评分（减1是因为评分是从1开始的，而颜色索引是从0开始的）获取对应的颜色索引\n",
    "color_indices = df_embedded.Score.values - 1\n",
    "\n",
    "# 确保你的数据点和颜色索引的数量匹配\n",
    "assert len(vis_dims) == len(df_embedded.Score.values)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Amazon ratings visualized in language using t-SNE')"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 创建一个基于预定义颜色的颜色映射对象\n",
    "colormap = matplotlib.colors.ListedColormap(colors)\n",
    "# 使用 matplotlib 创建散点图，其中颜色由颜色映射对象和颜色索引共同决定，alpha 是点的透明度\n",
    "plt.scatter(x, y, c=color_indices, cmap=colormap, alpha=0.3)\n",
    "\n",
    "# 为图形添加标题\n",
    "plt.title(\"Amazon ratings visualized in language using t-SNE\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**t-SNE降维后，评论大致分为3个大类。**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 4. 使用 K-Means 聚类，然后使用 t-SNE 可视化"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "# 从 scikit-learn中导入 KMeans 类。KMeans 是一个实现 K-Means 聚类算法的类。\n",
    "from sklearn.cluster import KMeans\n",
    "\n",
    "# np.vstack 是一个将输入数据堆叠到一个数组的函数（在垂直方向）。\n",
    "# 这里它用于将所有的 ada_embedding 值堆叠成一个矩阵。\n",
    "# matrix = np.vstack(df.ada_embedding.values)\n",
    "\n",
    "# 定义要生成的聚类数。\n",
    "n_clusters = 4\n",
    "\n",
    "# 创建一个 KMeans 对象，用于进行 K-Means 聚类。\n",
    "# n_clusters 参数指定了要创建的聚类的数量；\n",
    "# init 参数指定了初始化方法（在这种情况下是 'k-means++'）；\n",
    "# random_state 参数为随机数生成器设定了种子值，用于生成初始聚类中心。\n",
    "# n_init=10 消除警告 'FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4'\n",
    "kmeans = KMeans(n_clusters = n_clusters, init='k-means++', random_state=42, n_init=10)\n",
    "\n",
    "# 使用 matrix（我们之前创建的矩阵）来训练 KMeans 模型。这将执行 K-Means 聚类算法。\n",
    "kmeans.fit(matrix)\n",
    "\n",
    "# kmeans.labels_ 属性包含每个输入数据点所属的聚类的索引。\n",
    "# 这里，我们创建一个新的 'Cluster' 列，在这个列中，每个数据点都被赋予其所属的聚类的标签。\n",
    "df_embedded['Cluster'] = kmeans.labels_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "12     1\n",
       "13     1\n",
       "14     1\n",
       "15     3\n",
       "16     1\n",
       "      ..\n",
       "447    2\n",
       "436    2\n",
       "437    0\n",
       "438    2\n",
       "439    1\n",
       "Name: Cluster, Length: 1000, dtype: int32"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_embedded['Cluster']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ProductId</th>\n",
       "      <th>UserId</th>\n",
       "      <th>Score</th>\n",
       "      <th>Summary</th>\n",
       "      <th>Text</th>\n",
       "      <th>combined</th>\n",
       "      <th>n_tokens</th>\n",
       "      <th>embedding</th>\n",
       "      <th>embedding_vec</th>\n",
       "      <th>Cluster</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>B000K8T3OQ</td>\n",
       "      <td>AK43Y4WT6FFR3</td>\n",
       "      <td>1</td>\n",
       "      <td>Broken in a million pieces</td>\n",
       "      <td>Chips were broken into small pieces. Problem i...</td>\n",
       "      <td>Title: Broken in a million pieces; Content: Ch...</td>\n",
       "      <td>120</td>\n",
       "      <td>[-0.0005399271612986922, -0.004124758299440145...</td>\n",
       "      <td>[-0.0005399271612986922, -0.004124758299440145...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>B0051C0J6M</td>\n",
       "      <td>AWFA8N9IXELVH</td>\n",
       "      <td>1</td>\n",
       "      <td>Deceptive description</td>\n",
       "      <td>On Oct 9 I ordered from a different vendor the...</td>\n",
       "      <td>Title: Deceptive description; Content: On Oct ...</td>\n",
       "      <td>157</td>\n",
       "      <td>[0.0068963742814958096, 0.0167608093470335, -0...</td>\n",
       "      <td>[0.0068963742814958096, 0.0167608093470335, -0...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     ProductId         UserId  Score                     Summary  \\\n",
       "12  B000K8T3OQ  AK43Y4WT6FFR3      1  Broken in a million pieces   \n",
       "13  B0051C0J6M  AWFA8N9IXELVH      1       Deceptive description   \n",
       "\n",
       "                                                 Text  \\\n",
       "12  Chips were broken into small pieces. Problem i...   \n",
       "13  On Oct 9 I ordered from a different vendor the...   \n",
       "\n",
       "                                             combined  n_tokens  \\\n",
       "12  Title: Broken in a million pieces; Content: Ch...       120   \n",
       "13  Title: Deceptive description; Content: On Oct ...       157   \n",
       "\n",
       "                                            embedding  \\\n",
       "12  [-0.0005399271612986922, -0.004124758299440145...   \n",
       "13  [0.0068963742814958096, 0.0167608093470335, -0...   \n",
       "\n",
       "                                        embedding_vec  Cluster  \n",
       "12  [-0.0005399271612986922, -0.004124758299440145...        1  \n",
       "13  [0.0068963742814958096, 0.0167608093470335, -0...        1  "
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_embedded.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 首先为每个聚类定义一个颜色。\n",
    "colors = [\"red\", \"green\", \"blue\", \"purple\"]\n",
    "\n",
    "# 然后，你可以使用 t-SNE 来降维数据。这里，我们只考虑 'embedding_vec' 列。\n",
    "tsne_model = TSNE(n_components=2, random_state=42)\n",
    "vis_data = tsne_model.fit_transform(matrix)\n",
    "\n",
    "# 现在，你可以从降维后的数据中获取 x 和 y 坐标。\n",
    "x = vis_data[:, 0]\n",
    "y = vis_data[:, 1]\n",
    "\n",
    "# 'Cluster' 列中的值将被用作颜色索引。\n",
    "color_indices = df_embedded['Cluster'].values\n",
    "\n",
    "# 创建一个基于预定义颜色的颜色映射对象\n",
    "colormap = matplotlib.colors.ListedColormap(colors)\n",
    "\n",
    "# 使用 matplotlib 创建散点图，其中颜色由颜色映射对象和颜色索引共同决定\n",
    "plt.scatter(x, y, c=color_indices, cmap=colormap)\n",
    "\n",
    "# 为图形添加标题\n",
    "plt.title(\"Clustering visualized in 2D using t-SNE\")\n",
    "\n",
    "# 显示图形\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**K-MEANS 聚类可视化效果，4类（官方介绍：一个专注于狗粮，一个专注于负面评论，两个专注于正面评论）。**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 5. 使用 Embedding 进行文本搜索"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![cosine](images/cosine.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "# cosine_similarity 函数计算两个嵌入向量之间的余弦相似度。\n",
    "def cosine_similarity(a, b):\n",
    "    return np.dot(a, b) / (np.linalg.norm(a) * np.linalg.norm(b))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "list"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(df_embedded[\"embedding_vec\"][0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 定义一个名为 search_reviews 的函数，\n",
    "# Pandas DataFrame 产品描述，数量，以及一个 pprint 标志（默认值为 True）。\n",
    "def search_reviews(df, product_description, n=3, pprint=True):\n",
    "    product_embedding = embedding_text(product_description)\n",
    "    \n",
    "    df[\"similarity\"] = df.embedding_vec.apply(lambda x: cosine_similarity(x, product_embedding))\n",
    "\n",
    "    results = (\n",
    "        df.sort_values(\"similarity\", ascending=False)\n",
    "        .head(n)\n",
    "        .combined.str.replace(\"Title: \", \"\")\n",
    "        .str.replace(\"; Content:\", \": \")\n",
    "    )\n",
    "    if pprint:\n",
    "        for r in results:\n",
    "            print(r[:200])\n",
    "            print()\n",
    "    return results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Good Buy:  I liked the beans. They were vacuum sealed, plump and moist. Would recommend them for any use. I personally split and stuck them in some vodka to make vanilla extract. Yum!\n",
      "\n",
      "Jamaican Blue beans:  Excellent coffee bean for roasting. Our family just purchased another 5 pounds for more roasting. Plenty of flavor and mild on acidity when roasted to a dark brown bean and befor\n",
      "\n",
      "Delicious!:  I enjoy this white beans seasoning, it gives a rich flavor to the beans I just love it, my mother in law didn't know about this Zatarain's brand and now she is traying different seasoning\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# 使用 'delicious beans' 作为产品描述和 3 作为数量，\n",
    "# 调用 search_reviews 函数来查找与给定产品描述最相似的前3条评论。\n",
    "# 其结果被存储在 res 变量中。\n",
    "res = search_reviews(df_embedded, 'delicious beans', n=3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Healthy Dog Food:  This is a very healthy dog food. Good for their digestion. Also good for small puppies. My dog eats her required amount at every feeding.\n",
      "\n",
      "Doggy snacks:  My dog loves these snacks. However they are made in China and as far as I am concerned, suspect!!!! I found an abundance of American made ,human grade chicken dog snacks. Just Google fo\n",
      "\n",
      "Dogs Love Them!:  My Maltese and Cavalier King Charles love these treats!  I feel good about feeding them a healthier treat.<br />Not made in China!\n",
      "\n"
     ]
    }
   ],
   "source": [
    "res = search_reviews(df_embedded, 'dog food', n=3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "God Awful:  As a dabbler who enjoys spanning the entire spectrum of taste, I am more than willing to try anything once.  Both as a food aficionado and a lover of bacon, I just had to pick this up.  On\n",
      "\n",
      "Disappointed:  The metal cover has severely disformed. And most of the cookies inside have been crushed into small pieces. Shopping experience is awful. I'll never buy it online again.\n",
      "\n",
      "Just Bad:  Watery and unpleasant.  Like Yoohoo mixed with dirty dish water.  I find it quite odd that Keurig would release a product like this.  I'm sure they can come up with a decent hot chocolate a\n",
      "\n",
      "Arrived in pieces:  Not pleased at all. When I opened the box, most of the rings were broken in pieces. A total waste of money.\n",
      "\n",
      "Awesome:  They arrived before the expected time and were of fantastic quality. Would recommend to any one looking for a awesome treat\n",
      "\n"
     ]
    }
   ],
   "source": [
    "res = search_reviews(df_embedded, 'awful', n=5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Healthy Dog Food:  This is a very healthy dog food. Good for their digestion. Also good for small puppies. My dog eats her required amount at every feeding.\n",
      "\n",
      "Doggy snacks:  My dog loves these snacks. However they are made in China and as far as I am concerned, suspect!!!! I found an abundance of American made ,human grade chicken dog snacks. Just Google fo\n",
      "\n",
      "Dogs Love Them!:  My Maltese and Cavalier King Charles love these treats!  I feel good about feeding them a healthier treat.<br />Not made in China!\n",
      "\n"
     ]
    }
   ],
   "source": [
    "def search_reviews(df, product_description, n=3, pprint=True):\n",
    "    product_embedding = embedding_text(product_description)\n",
    "\n",
    "    df[\"similarity\"] = df.embedding_vec.apply(lambda x: cosine_similarity(x, product_embedding))\n",
    "\n",
    "    results = (\n",
    "        df.sort_values(\"similarity\", ascending=False)\n",
    "        .head(n)\n",
    "        .combined.str.replace(\"Title: \", \"\")\n",
    "        .str.replace(\"; Content:\", \": \")\n",
    "    )\n",
    "    if pprint:\n",
    "        for r in results:\n",
    "            print(r[:200])\n",
    "            print()\n",
    "    return results\n",
    "\n",
    "res = search_reviews(df_embedded, 'dog food', n=3)"
   ]
  },
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   "metadata": {},
   "outputs": [],
   "source": []
  }
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